6.5420 Randomness and Computation (Spring 2026)
- Instructor:
Ronitt Rubinfeld
- Teaching Assistant:
Lily Chung
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Course email: 6-5420-staff lists csail mit edu (with at and dots in proper places)
- Lectures: Tuesdays and Thursdays, 11:00-12:30 in 32-144
- Office hours: Fridays at 4pm in 32-G634
Brief Course description:
We study the power and sources of randomness in computation, concentrating on connections and applications to computational complexity, computational learning theory, cryptography and combinatorics.
Topics include:
(1) Basic tools: probabilistic, proofs, Lovász local lemma, uniform generation and approximate counting, Fourier analysis, influence of variables on functions, random walks, graph expansion, Szemeredi regularity lemma.
(2) Randomness vs. Predictability: pseudorandom generators, weak random sources, derandomization and recycling randomness, computational learning theory, Fourier based learning algorithms, weak vs. strong learning, boosting, average vs. worst case hardness, XOR lemma.
Course information handout.
Tentative pset and quiz dates.
Announcements:
Lecture Notes:
Homework:
Homework submission: Gradescope (details on Piazza).
Useful information:
- References on Markov, Chebyshev and tail inequalities:
- Texts:
- Information for scribes:
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Instructions for graders.
Signup for graders: Link on Piazza.